Evaluation of Sweet Sauce Characteristic Taste Based on Electronic Tongue Technology

2012 ◽  
Vol 554-556 ◽  
pp. 1593-1601
Author(s):  
Ming Quan Huang ◽  
Lu Wang ◽  
Bao Guo Sun ◽  
Hong Yu Tian
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Reducing Sugars ◽  
Electronic Tongue ◽  
Amino Nitrogen ◽  
Physicochemical Characterization ◽  
Principal Component ◽  
On Line

A commercial electronic tongue (ET) with specific sensors was applied on taste distinction and physicochemical characterization of seven kinds of sweet sauces. The response signals of ET sensors were analyzed by Principal Component Analysis (PCA) and Discriminant Factor Analysis (DFA). Meanwhile, these signals were transformed into the four relative taste scores (sourness, saltiness, umami and sweetness) by macro operation, followed by comparing with the corresponding four physiochemical indexes (total acids, sodium chloride, amino nitrogen and reducing sugars) which were determined by the methods in GB/T. The results show that ET can be used to distinguish different kinds of sweet sauces according to overall taste. Moreover, the intensity order of taste scores that obtained from ET is basically matched with the sequence of the corresponding physicochemical indexes, which proves that ET technique can be an effective approach to monitor and guarantee the quality of sweet sauce on line.

scholarly journals Use of multivariate statistics to predict the physicochemical quality of milk

2020 ◽  
Vol 9 (4) ◽  
pp. e41942808
Author(s):  
Lenara Oliveira Pinheiro ◽  
Mário Roberto Júnior ◽  
Clara Mariana Gonçalves Lima ◽  
Heliara Caires Sousa ◽  
Jorge Pamplona Pagnossa ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Raw Milk ◽  
Dry Extract ◽  
Quality Of Food ◽  
Quality Of Milk ◽  
Main Components ◽  
Extract Protein

Multivariate analysis involves the application of statistical and computational methods to predict responses. Among the various methods of statistical analysis multivariate, the analysis by main components is highlighted to predict the composition and quality of food in general. The objective of this work was to characterize the milk producers of the municipality of Itapetinga-BA, using principal component analysis. Twenty samples of raw milk were used, collected at the reception of the dairy located in Itapetinga-BA. The variables analyzed were: fat, density, defatted dry extract, protein and lactose. The first two main components explained 87.24% of the total variation. It was verified the formation of different groups distributed in the four quadrants of the system. First quadrant stood out from the others by forming a group composed of ten producers in the analyzed region, characterized by presenting samples with higher lactose content and lower fat content in milk. The lactose and fat variables are of greater importance in the characterization of milk.

Detection of the Chinese Rice Wine Using an Electronic Tongue

2014 ◽  
Vol 1044-1045 ◽  
pp. 937-940
Author(s):  
Xiao Li Lu ◽  
Xiao Qing Cai
Keyword(s):  
Neural Network ◽  
Principal Component Analysis ◽  
Artificial Neural Network ◽  
Factor Analysis ◽  
Electronic Tongue ◽  
Principal Component ◽  
Rice Wine ◽  
Chinese Rice Wine ◽  
Artificial Neural Network Ann ◽  
Accuracy Of Prediction

An electronic tongue was employed to detect different brands of Chinese rice wine. The results showed that all of the seven classes of Chinese rice wine can be discriminated by Discriminant Factor Analysis (DFA) and Principal Component Analysis (PCA). Based on Artificial Neural Network (ANN), the electronic tongue can predict the marked age of Chinese rice wine, and the accuracy of prediction was above 90% averagely.

scholarly journals Driving Factors of Consumer to Purchase Furniture Online on IKEA Indonesia Website

2018 ◽  
Vol 2 (1) ◽  
pp. 19
Author(s):  
Trisha Gilang Saraswati
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Perceived Risk ◽  
Online Shopping ◽  
Principal Component ◽  
Influential Factors ◽  
Driving Factors ◽  
Analysis Method ◽  
Long Time

The tendency of consumers in shopping for furniture is very different from shopping for other goods or services, because furniture is expected to be stored and used in a long time. Considering that, consumers tend to want to shop directly to offline stores in order to see, feel and check quality directly because of many aspects that are assessed such as the quality of materials, models, colors and more. Behind the trend to shop furniture offline, IKEA continues to innovate to improve the performance of its website so that consumers can shop online. Therefore, this study intends to analyze what factors are driving consumers in shopping for furniture online especially on the website of IKEA Indonesia. From two grounded theory employed on this research, there are 14 factors that can influence consumers to buy online. This data analysis uses Principal Component Analysis (PCA), a factor analysis method that extracts factors by using total variance in the analysis. From data calculation, it is known that there are 8 driving factors of consumer to purchase furniture online on IKEA Indonesia’s website: Enjoyment, Perceived Risk, Efficiency, Service & Merchandise Quality, Ease of Navigation, Price Attractiveness, Flexibility and Reliability. By knowing what factors can affect consumers in doing online shopping for furniture, companies in this case IKEA Indonesia can optimize the use of its website in accordance with influential factors.

scholarly journals Physicochemical Quality of Kernels from Terminalia catappa L. and Sensory Evaluation of the Concocted Kernels

2012 ◽  
Vol 1 (2) ◽  
pp. 1 ◽  
Author(s):  
Godi H. M. Biego ◽  
Amoin G. Konan ◽  
Togba E. Douati ◽  
L. P. Kouadio
Keyword(s):  
Sensory Evaluation ◽  
Reducing Sugars ◽  
Physicochemical Characterization ◽  
Preference Order ◽  
Total Sugars ◽  
Terminalia Catappa ◽  
Peroxide Values ◽  
Sensory Profiles

<p>This study focused on the physicochemical characterization of the kernels from <em>Terminalia catappa</em> L. and sensory evaluation of appetizers concocted from these kernels. The results of the physicochemical analyzes were as follow: ash (4.0±0.1%), proteins (40.9±1.3%), lipids (50.6±1.0%), total sugars (1.4±0.1%), reducing sugars (0.3±0.01%) and moisture content (3.8±0.4%). Acid and peroxide values were respectively 1.3±0.2% and 6.30±0.23 meq O<sub>2</sub>/kg oil. Two appetizers were concocted from the fresh kernels of <em>Terminalia catappa</em> L: Salted Roasted Kernels (SRK) and Unsalted Roasted Kernels (URK). A comparison of sensory profiles of both appetizers showed that they were not significantly different (p&lt;5%) for the parameters sweet and oily but different (p&lt;5%) for the parameters salty, bitter and firm. However, the tasters’ preference for the Salted Roasted Kernels was not significantly different from their preference for the Unsalted Roasted Kernels. The appetizers from <em>Terminalia catappa</em> L. (SRK and URK) were then compared to other appetizers readily available in markets and malls: Salted Roasted Peanuts (SRP), Unsalted Roasted Peanuts (URP), Unsalted Roasted Hazelnuts (URH) and Salted Roasted Cashew nuts (SRC). The preference order was: URH&lt;URK&lt;SRK&lt;URP&lt;SRC&lt;SRP.</p>

scholarly journals Effective discrimination of flavours and tastes of Chinese traditional fish soups made from different regions of the silver carp using an electronic nose and electronic tongue

2020 ◽  
Vol 38 (No. 2) ◽  
pp. 84-93
Author(s):  
Zhengyi Hu ◽  
Yao Tong ◽  
Anne Manyande ◽  
Hongying Du
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Electronic Nose ◽  
Theoretical Basis ◽  
Silver Carp ◽  
Electronic Tongue ◽  
Principal Component ◽  
Chemical Components ◽  
Sds Page ◽  
Carp Fish

Silver carp is a one of the most important freshwater fish species in China, and is popular when making soup in the Chinese dietary culture. In order to investigate the profile of fish soup tastes and flavours cooked using different regions of the same fish, the silver carp was cut into four different regions: head, back, abdomen, and tail. The differences in taste and flavour of the four kinds of homemade fish soup were investigated by an electronic nose and electronic tongue. The basic chemical components of the different fish regions and the SDS-PAGE profile of the fish soup samples were investigated. Two chemometrics methods (principal component analysis and discriminant factor analysis) were used to classify the odour and taste of the fish soup samples. The results showed that the electronic tongue and nose performed outstandingly in discriminating the four fish soups even though the samples were made from different regions of the same fish. The taste and flavour information of different regions of the silver carp fish could provide the theoretical basis for food intensive processing.<br /><br />

Generic monitoring tools for water characteristics assessment

2003 ◽  
Vol 3 (1-2) ◽  
pp. 351-357
Author(s):  
S. Le Bonté ◽  
M.-N. Pons ◽  
O. Potier ◽  
S. Chanel ◽  
M. Baklouti
Keyword(s):  
Municipal Wastewater ◽  
Principal Component ◽  
Toxic Substances ◽  
Capacity Curves ◽  
Water Characteristics ◽  
Monitoring Tools ◽  
Visible Spectra ◽  
On Line ◽  
Mining Procedure

An adaptive principal component analysis applied to sets of data provided by global analytical methods (UV-visible spectra, buffer capacity curves, respirometric tests) is proposed as a generic procedure for on-line and fast characterization of wastewater. The data-mining procedure is able to deal with a large amount of information, takes into account the normal variations of wastewater composition related to human activity, and enables a rapid detection of abnormal situations such as the presence of toxic substances by comparison of the actual wastewater state with a continuously updated reference. The procedure has been validated on municipal wastewater.

scholarly journals Exploratory Monitoring of the Quality and Authenticity of Commercial Honey in Ecuador

Foods ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 105 ◽  
Author(s):  
Lorena Salvador ◽  
Michelle Guijarro ◽  
Daniela Rubio ◽  
Bolívar Aucatoma ◽  
Tanya Guillén ◽  
...  
Keyword(s):  
Honey Bees ◽  
Reducing Sugars ◽  
Conductivity Measurement ◽  
Principal Component ◽  
Economic Importance ◽  
Critical Problem ◽  
Spectroscopic Analyses ◽  
Chemical Threats ◽  
Raman And Ir Spectroscopy

Honey is one of the oldest sweetening foods and has economic importance, making this product attractive to adulteration with cheap sugars. This can cause a critical problem in the honey industry and a possible health risk. The present work has the aim of evaluating the authenticity of honey commercialized in two different provinces of Ecuador (Pichincha and Loja) by performing physicochemical and spectroscopic analyses. For this study 25 samples were collected from different places and markets and characterized by water, sucrose, reducing sugars and electric conductivity measurement. Also, their Raman and Infrared (IR) spectra were recorded and analysed using a Principal Component Analysis (PCA) in order to verify the quality of the honeys. In addition, a screening of several pesticides was performed in order to verify possible chemical threats to human health and honey bees. It was found that 8 samples have a deviation from the Standard established parameters. Two of them have a high difference in the content of sucrose and reducing sugars, which are located deviated from all the other samples in the PCA of the applied vibrational spectroscopy (IR/Raman), shaping two clear clusters. The results show that Raman and IR spectroscopy is appropriate techniques for the quality control of honey and correlates well with the physicochemical analyses.

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